Other articles


  1. Data Visualization (Python)

    Data Visualization With Python

    There are a lot of good code that makes it easy to tell a story with your data.

    Libraries

    I list some popular libraries to deal with:

    1. matplotlib
    2. seaborn
    3. plotly ...

    Example 1

    I have written a sript a while ago to plot a long sequence of data. In this first example I plot data represented LIDAR scanning of a road with segments having either cleanded ditches or not, while registering a lot I am intrested here in representing three quantitative variables extracted from LIDAR pointcloud.

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  2. Clustering

    Intro

    Cluster analysis is the method in data analysis that is used to classify data points. Clustering pick out pattern in unlabeled data and group items in meaningful way. As a programmer you have to write scripts that learns the inherent structure of the data with no labeled examples provided (unsupervised learning). The program under the hood analyzes the data it encounters and tries to identify patterns and group the data on output.

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  3. Perlin Noise

    Perlin Noise Algoritm

    Ken Perlin is the creator of perlin noise algoritm used in generating textures and terrain-like images to name a few applications of this smooth noise. This arcticle is about application of it and not so much about the algorithms steps.

    Perlin in Python

    In Python in 2023 there is no built-in implementation of the Perlin noise algorithm. Since I can't quickly (time isn't a key factor) refactor this implementation from java to python https://mrl.cs.nyu.edu/~perlin/noise/ read more

  4. Understanding Probability With Python

    Published: Fri 09 December 2022
    By Alex

    In python.

    Probability is a branch of mathematics that is often used to make decisions and is concerned with measuring uncertainty.

    Introduction

    Sets

    Set data types in Python have rules similar to set in mathematics: collections are unordered, unchangeable (only removal or addition is applicable), store unique items, and are unindexed.

    Experiments and Event

    Experiment return values for observation(s), and observations have some level of uncertainty. Single possible outcome of an experiment is a sample point in a set called sample space. Set sample space stores all possible sample points for one experiment. If your experiment is a set of n sample points the full sample space is written as follows for example of coin flip:

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  5. Statistical Distributions (Common ones)

    Published: Mon 17 October 2022
    By Alex

    In python.

    Introduction

    A probability distribution in statistics is a function that returns the possible values for a variable with different occurence rate (how often values occur). Distribution in nature and society tend to fit pattern with ocasionally occuring exceptions (isn't absence of pattern is a pattern too?).

    Probability Mass Function

    Discrete random variable has probability mass function (PMF) being a particular type of probability distribution read more

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